Design of Computer Programs



Informazione importanti

  • Corso
  • Online
  • Quando:

Learn how to model problems, and how to optimize performance by using some of the advanced features of Python.

Informazione importanti

Dove e quando

Inizio Luogo

Cosa impari in questo corso?

Language Programming
Programming Application
Computer Programs



Approx. 2 months

Join thousands of students Course Summary

Understanding how to approach programming problems and devise a solution is an essential skill for any Python developer. In this course, you’ll learn new concepts, patterns, and methods that will expand your coding abilities from programming expert, Peter Norvig.

Why Take This Course?

Move along the path towards becoming an expert programmer! In this class you will practice going from a problem description to a solution, using a series of assignments. During office hours segments, Peter will also share his own personal tips and tricks for approaching programming problems - and his techniques may surprise you!

Prerequisites and Requirements

This course is intended for experienced Python programmers; students should be familiar with the Python syntax, as well as familiar with the following programming concepts: data structures, basic algorithms, and lambda functions.

This course is intended to challenge you. Be ready to struggle (and learn)!

See the Technology Requirements for using Udacity.

Syllabus Lesson 1: Winning Poker Hands

Steps of the design process; Developing for clarity and generality; Arguments for program correctness; Experimentation and simulation.; Design tradeoffs; Simplicity and Clarity. Decomposition and composability.

Lesson 2: Back of the Envelope

Back of envelope calculations; When to use brute force and when to be clever; The Zebra puzzle; Generator expressions; Permutations and combinations. Cryptarithmetic; Recursive and wishful thinking; Longest palindrome substring algorithm.

Lesson 3: Regular Expressions, other languages and interpreters

Defining the language of regular expressions; Interpreting the language; Defining the set of strings matched by a regular expression;
Other languages.

Lesson 4: Dealing with complexity through search

Search: finding your way with a flashlight or boat; pouring water. Analyzing the efficiency of an algorithm; Recurrence relations; Matching data types with algorithms.

Lesson 5: Dealing with uncertainty through probability

Probability: the game of Pig; Maximizing expected utility to optimize strategy.

Lesson 6: Word Games

Managing complexity; Large sets of words; Appropriate data structures; Word games.

Lesson 7: Conclusion

Interviews and Practice Exam